In a context where nearly 80% of companies report having suffered at least one fraud attempt and where this growing phenomenon affects all entities, regardless of their sector of activity, location or turnover, the use of innovative technological solutions is a valuable aid for CFOs (administrative and financial departments).
Innovative technologies to support internal anti-fraud measures
Fraud affects all companies, including those specialising in security or in sensitive sectors, and no one is immune.
All the players have therefore gradually mobilised to raise awareness among the entities under threat: the State, through specialised sites made available to companies, and the banks, by strengthening their vigilance and their warning systems for these same players.
But it is internally that the anti-fraud measures have been improved the most, in particular through awareness-raising actions and even increased training for all staff who are directly or indirectly concerned by these risks.
In parallel with these actions, the implementation of technological solutions capable of supporting the financial departments has become increasingly urgent.
Thus, the use of scalable devices capable of adapting quickly to the various anti-fraud issues, starting with the management of Big Data[1], is now essential.
« Machine learning » to the rescue of risk analysis
In addition to tools adapted to the processing of massive data, Machine Learning has been added to the solutions that enable us to move from data processing (input) to its analysis and even to recommendations (output) based on the development of evolving algorithms.
In the context of the fight against fraud, these predictive capabilities make it possible to exploit the financial behaviour of the company’s partners, particularly in terms of the frequency of payment to a supplier, the number of users for a specific type of payment or the frequency of use of the same IBAN[2] (bank details).
In addition to their potential for detecting fraud, these technologies also allow financial departments to refine their risk management, for example by assigning a score per IBAN according to various criteria specific to the company itself.
In addition to strengthening security, these tools also create new opportunities and even open up fields of action that would not have been possible with traditional IT tools.
The enhanced expertise of a combination of human and multi-channel technology
However, this anti-fraud campaign cannot remain effective without, in addition to the mobilisation of all the players, the intervention of experts who have mastered both risk management and the technological tools used.
When a new customer or service provider is registered, for example, or when a new IBAN appears for an old service provider, it is indeed essential to continue to carry out a “manual” investigation to prevent any risk of fraud.
Similarly, the development of dematerialised tools (in the cloud), in the area of factoring for example, where the IBAN transmitted to the financial department does not belong to the supplier but to its financial service provider, requires the analysis channels to be crossed.
Finally, with the help of these innovative tools, the audit teams can also collect information with greater added value, in addition to greater reliability.
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[1] Also known as “megadata”, big data refers to a set of data so voluminous that it exceeds human intuition and analysis capabilities as well as conventional database or information management tools. Source: Wikipedia
[2] International Bank Account Number
